{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\perezeo\Dropbox\Language, Gender & Politics\Estonia\Language and Ethnic\JEPS\Final\JEPS_replication\Study1_analysis_log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}16 Aug 2018, 06:50:59

{com}. do "C:\Users\perezeo\Dropbox\Language, Gender & Politics\Estonia\Language and Ethnic\JEPS\Final\JEPS_replication\Study1_analysis.do"
{txt}
{com}. ****************************************************************************************************************************
. ***  PROJECT:  "Language Heightens the Political Salience of Ethnic Divisions", Journal of Experimental Political Science
. ***  AUTHORS: Efren O. Perez and Margit Tavits
. ***  DESCRIPTION: Stata code to replicate results from Study 1
. ***  DATE: June 6, 2018
. ****************************************************************************************************************************
. 
. 
. ********************************************************
. **Section 1: setting up the data for the analysis ******
. ********************************************************
. 
. set more off
{txt}
{com}. 
. *** Generate "age"
. gen age=how_old 
{txt}
{com}. 
. ***Generate "Russian as first language"
. gen russfirst=0
{txt}
{com}. recode russfirst (0=1) if first_lg==1
{txt}(russfirst: 99 changes made)

{com}. tab russfirst

  {txt}russfirst {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        163       62.21       62.21
{txt}          1 {c |}{res}         99       37.79      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        262      100.00
{txt}
{com}. 
. ***Generate "female"
. gen female=0
{txt}
{com}. recode female (0=1) if gender==1
{txt}(female: 140 changes made)

{com}. tab female

     {txt}female {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        122       46.56       46.56
{txt}          1 {c |}{res}        140       53.44      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        262      100.00
{txt}
{com}. 
. ***Generate "Prefer russian interview"
. gen prefruss=0
{txt}
{com}. recode prefruss (0=1) if preferred_lg==2
{txt}(prefruss: 82 changes made)

{com}. tab prefruss

   {txt}prefruss {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        180       68.70       68.70
{txt}          1 {c |}{res}         82       31.30      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        262      100.00
{txt}
{com}. 
. ***Generate "education" and "college"
. gen edu=education
{txt}
{com}. 
. gen college=0
{txt}
{com}. recode college (0=1) if edu==4
{txt}(college: 15 changes made)

{com}. recode college (0=1) if edu==5
{txt}(college: 90 changes made)

{com}. tab college

    {txt}college {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        157       59.92       59.92
{txt}          1 {c |}{res}        105       40.08      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        262      100.00
{txt}
{com}. 
. ***Generate "assigned interview language" (treatment)
. gen eston=0
{txt}
{com}. recode eston (0=1) if assigned_lg==1
{txt}(eston: 116 changes made)

{com}. 
. gen russian=0
{txt}
{com}. recode russian (0=1) if assigned_lg==2
{txt}(russian: 146 changes made)

{com}. 
. ***Generate "Importance of integration"
. generate integration = 1
{txt}
{com}. recode integration 1=4 if issue_a==3
{txt}(integration: 19 changes made)

{com}. recode integration 1=3 if issue_b==3
{txt}(integration: 39 changes made)

{com}. recode integration 1=2 if issue_c==3
{txt}(integration: 81 changes made)

{com}. summarize integration

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}integration {c |}{res}        262    1.824427    .9385806          1          4
{txt}
{com}. 
. 
. ****************************************************
. **Section 2: Analyses in the main text and SI ******
. ****************************************************
. 
. ***Table 1, main text
. ***Model 1
. ologit integration russian

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.64682}  
Iteration 2:{space 3}log likelihood = {res:-310.64583}  
Iteration 3:{space 3}log likelihood = {res:-310.64583}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      3.18
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0747
{txt}Log likelihood = {res}-310.64583{txt}{col 49}Pseudo R2{col 67}= {res}    0.0051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .4165536{col 26}{space 2} .2346692{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.0433896{col 67}{space 3} .8764968
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .1113242{col 26}{space 2} .1818716{col 54}{space 4}-.2451377{col 67}{space 3}  .467786
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.505565{col 26}{space 2} .2067364{col 54}{space 4} 1.100369{col 67}{space 3}  1.91076
{txt}       /cut3 {c |}{col 14}{res}{space 2}  2.80099{col 26}{space 2} .2799122{col 54}{space 4} 2.252373{col 67}{space 3} 3.349608
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ***Calculate substantive effects and p-values for main text
. ologit integration i.russian

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.64682}  
Iteration 2:{space 3}log likelihood = {res:-310.64583}  
Iteration 3:{space 3}log likelihood = {res:-310.64583}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      3.18
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0747
{txt}Log likelihood = {res}-310.64583{txt}{col 49}Pseudo R2{col 67}= {res}    0.0051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.russian {c |}{col 14}{res}{space 2} .4165536{col 26}{space 2} .2346692{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.0433896{col 67}{space 3} .8764968
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .1113242{col 26}{space 2} .1818716{col 54}{space 4}-.2451377{col 67}{space 3}  .467786
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.505565{col 26}{space 2} .2067364{col 54}{space 4} 1.100369{col 67}{space 3}  1.91076
{txt}       /cut3 {c |}{col 14}{res}{space 2}  2.80099{col 26}{space 2} .2799122{col 54}{space 4} 2.252373{col 67}{space 3} 3.349608
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins russian, predict(outcome(1))
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}       262
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(integration==1), predict(outcome(1))}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}
{space 10}0  {c |}{col 14}{res}{space 2} .5278023{col 26}{space 2} .0453273{col 37}{space 1}   11.64{col 46}{space 3}0.000{col 54}{space 4} .4389624{col 67}{space 3} .6166423
{txt}{space 10}1  {c |}{col 14}{res}{space 2} .4242796{col 26}{space 2} .0392833{col 37}{space 1}   10.80{col 46}{space 3}0.000{col 54}{space 4} .3472857{col 67}{space 3} .5012735
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(russian) predict(outcome(1))
{res}
{txt}Conditional marginal effects{col 49}Number of obs{col 67}= {res}       262
{txt}Model VCE{col 14}: {res}OIM

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(integration==1), predict(outcome(1))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.russian}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.russian {c |}{col 14}{res}{space 2}-.1035227{col 26}{space 2} .0579834{col 37}{space 1}   -1.79{col 46}{space 3}0.074{col 54}{space 4} -.217168{col 67}{space 3} .0101226
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. 
. ***Model 2
. ologit integration russian prefruss 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.59036}  
Iteration 2:{space 3}log likelihood = {res:-310.58926}  
Iteration 3:{space 3}log likelihood = {res:-310.58926}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      3.29
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1931
{txt}Log likelihood = {res}-310.58926{txt}{col 49}Pseudo R2{col 67}= {res}    0.0053

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2}  .416749{col 26}{space 2} .2347032{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.0432608{col 67}{space 3} .8767588
{txt}{space 4}prefruss {c |}{col 14}{res}{space 2}-.0847387{col 26}{space 2} .2521784{col 37}{space 1}   -0.34{col 46}{space 3}0.737{col 54}{space 4}-.5789992{col 67}{space 3} .4095219
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .0857445{col 26}{space 2} .1970554{col 54}{space 4} -.300477{col 67}{space 3} .4719659
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.480716{col 26}{space 2}  .219351{col 54}{space 4} 1.050796{col 67}{space 3} 1.910636
{txt}       /cut3 {c |}{col 14}{res}{space 2}  2.77586{col 26}{space 2} .2895222{col 54}{space 4} 2.208407{col 67}{space 3} 3.343314
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *************************
. ***Results in the SI ****
. *************************
. 
. ***Table SI.2.2: balance check
. 
. by eston, sort : summarize college

{txt}{hline}
-> eston = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}college {c |}{res}        146    .3972603    .4910152          0          1

{txt}{hline}
-> eston = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}college {c |}{res}        116    .4051724    .4930552          0          1

{txt}
{com}. tab college eston, chi2

           {txt}{c |}         eston
   college {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}        88         69 {txt}{c |}{res}       157 
{txt}         1 {c |}{res}        58         47 {txt}{c |}{res}       105 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       146        116 {txt}{c |}{res}       262 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0169  {txt} Pr = {res}0.897
{txt}
{com}. 
. by eston, sort : summarize female

{txt}{hline}
-> eston = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}female {c |}{res}        146    .5410959    .5000236          0          1

{txt}{hline}
-> eston = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}female {c |}{res}        116    .5258621     .501497          0          1

{txt}
{com}. tab female eston, chi2

           {txt}{c |}         eston
    female {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}        67         55 {txt}{c |}{res}       122 
{txt}         1 {c |}{res}        79         61 {txt}{c |}{res}       140 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       146        116 {txt}{c |}{res}       262 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0603  {txt} Pr = {res}0.806
{txt}
{com}. 
. by eston, sort : summarize age, detail

{txt}{hline}
-> eston = 0

                             age
{hline 61}
      Percentiles      Smallest
 1%    {res}       27             22
{txt} 5%    {res}       34             27
{txt}10%    {res}       40             28       {txt}Obs         {res}        146
{txt}25%    {res}       45             30       {txt}Sum of Wgt. {res}        146

{txt}50%    {res}     56.5                      {txt}Mean          {res} 55.54795
                        {txt}Largest       Std. Dev.     {res} 12.75449
{txt}75%    {res}       66             75
{txt}90%    {res}       72             76       {txt}Variance      {res}  162.677
{txt}95%    {res}       74             76       {txt}Skewness      {res}-.2661808
{txt}99%    {res}       76             76       {txt}Kurtosis      {res} 2.160968

{txt}{hline}
-> eston = 1

                             age
{hline 61}
      Percentiles      Smallest
 1%    {res}       24             23
{txt} 5%    {res}       28             24
{txt}10%    {res}       32             25       {txt}Obs         {res}        116
{txt}25%    {res}     42.5             25       {txt}Sum of Wgt. {res}        116

{txt}50%    {res}       54                      {txt}Mean          {res} 52.07759
                        {txt}Largest       Std. Dev.     {res} 13.56796
{txt}75%    {res}     61.5             74
{txt}90%    {res}       70             75       {txt}Variance      {res} 184.0896
{txt}95%    {res}       73             76       {txt}Skewness      {res}-.2677322
{txt}99%    {res}       76             76       {txt}Kurtosis      {res} 2.189532

{txt}
{com}. ranksum age, by(eston)

{txt}Two-sample Wilcoxon rank-sum (Mann-Whitney) test

       eston {c |}      obs    rank sum    expected
{hline 13}{c +}{hline 33}
           0 {c |}{res}{col 17}    146{col 26}   20397.5{col 38}     19199
           {txt}1 {c |}{res}{col 17}    116{col 26}   14055.5{col 38}     15254
{txt}{hline 13}{c +}{hline 33}
    combined {c |}{res}{col 17}    262{col 26}     34453{col 38}     34453

{txt}unadjusted variance{col 22}{res} 371180.67
{txt}adjustment for ties{col 22}{res}   -231.57
{txt}{col 22}{hline 10}
adjusted variance{col 22}{res} 370949.10

{txt}Ho: age(eston==0) = age(eston==1)
{col 14}z = {res}  1.968
{txt}{col 5}Prob > |z| = {res}  0.0491
{txt}
{com}. 
. by eston, sort : summarize russfirst

{txt}{hline}
-> eston = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}russfirst {c |}{res}        146     .369863    .4844293          0          1

{txt}{hline}
-> eston = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}russfirst {c |}{res}        116     .387931    .4893927          0          1

{txt}
{com}. tab russfirst eston, chi2

           {txt}{c |}         eston
 russfirst {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}        92         71 {txt}{c |}{res}       163 
{txt}         1 {c |}{res}        54         45 {txt}{c |}{res}        99 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       146        116 {txt}{c |}{res}       262 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0898  {txt} Pr = {res}0.764
{txt}
{com}. 
. by eston, sort : summarize prefruss

{txt}{hline}
-> eston = 0

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}prefruss {c |}{res}        146    .3150685    .4661423          0          1

{txt}{hline}
-> eston = 1

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}prefruss {c |}{res}        116    .3103448    .4646419          0          1

{txt}
{com}. tab prefruss eston, chi2

           {txt}{c |}         eston
  prefruss {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}       100         80 {txt}{c |}{res}       180 
{txt}         1 {c |}{res}        46         36 {txt}{c |}{res}        82 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       146        116 {txt}{c |}{res}       262 

{txt}          Pearson chi2({res}1{txt}) = {res}  0.0067  {txt} Pr = {res}0.935
{txt}
{com}. 
. 
. ***Table SI.2.3, randomization check
. 
. probit eston college female age russfirst prefruss

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-179.88323}  
Iteration 1:{space 3}log likelihood = {res: -177.3176}  
Iteration 2:{space 3}log likelihood = {res:-177.31669}  
Iteration 3:{space 3}log likelihood = {res:-177.31669}  
{res}
{txt}Probit regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}      5.13
{txt}{col 49}Prob > chi2{col 67}= {res}    0.3999
{txt}Log likelihood = {res}-177.31669{txt}{col 49}Pseudo R2{col 67}= {res}    0.0143

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       eston{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}college {c |}{col 14}{res}{space 2}-.0328148{col 26}{space 2} .1648244{col 37}{space 1}   -0.20{col 46}{space 3}0.842{col 54}{space 4}-.3558647{col 67}{space 3} .2902351
{txt}{space 6}female {c |}{col 14}{res}{space 2}-.0239988{col 26}{space 2} .1596604{col 37}{space 1}   -0.15{col 46}{space 3}0.881{col 54}{space 4}-.3369275{col 67}{space 3} .2889298
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0132911{col 26}{space 2} .0062002{col 37}{space 1}   -2.14{col 46}{space 3}0.032{col 54}{space 4}-.0254433{col 67}{space 3}-.0011389
{txt}{space 3}russfirst {c |}{col 14}{res}{space 2} .1492014{col 26}{space 2} .2764291{col 37}{space 1}    0.54{col 46}{space 3}0.589{col 54}{space 4}-.3925896{col 67}{space 3} .6909924
{txt}{space 4}prefruss {c |}{col 14}{res}{space 2}-.2089656{col 26}{space 2} .2924319{col 37}{space 1}   -0.71{col 46}{space 3}0.475{col 54}{space 4}-.7821216{col 67}{space 3} .3641905
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6062756{col 26}{space 2} .3757941{col 37}{space 1}    1.61{col 46}{space 3}0.107{col 54}{space 4}-.1302674{col 67}{space 3} 1.342819
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test college female age russfirst prefruss 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[eston]college = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [eston]female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [eston]age = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [eston]russfirst = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [eston]prefruss = 0{p_end}

{txt}{col 12}chi2(  5) ={res}    5.07
{txt}{col 10}Prob > chi2 =  {res}  0.4079
{txt}
{com}. 
. ***Table SI.2.6, robustness to covariates
. 
. ologit integration russian prefruss age

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res: -310.2286}  
Iteration 2:{space 3}log likelihood = {res:-310.22675}  
Iteration 3:{space 3}log likelihood = {res:-310.22675}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}3{txt}){col 67}= {res}      4.01
{txt}{col 49}Prob > chi2{col 67}= {res}    0.2599
{txt}Log likelihood = {res}-310.22675{txt}{col 49}Pseudo R2{col 67}= {res}    0.0064

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .3980336{col 26}{space 2} .2358692{col 37}{space 1}    1.69{col 46}{space 3}0.092{col 54}{space 4}-.0642615{col 67}{space 3} .8603287
{txt}{space 4}prefruss {c |}{col 14}{res}{space 2}-.0403987{col 26}{space 2} .2577773{col 37}{space 1}   -0.16{col 46}{space 3}0.875{col 54}{space 4} -.545633{col 67}{space 3} .4648356
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0078311{col 26}{space 2} .0092145{col 37}{space 1}    0.85{col 46}{space 3}0.395{col 54}{space 4} -.010229{col 67}{space 3} .0258912
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .5107899{col 26}{space 2} .5382644{col 54}{space 4}-.5441889{col 67}{space 3} 1.565769
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.908614{col 26}{space 2} .5509444{col 54}{space 4} .8287831{col 67}{space 3} 2.988445
{txt}       /cut3 {c |}{col 14}{res}{space 2} 3.206714{col 26}{space 2} .5860831{col 54}{space 4} 2.058012{col 67}{space 3} 4.355416
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ***Table SI.2.7 Mismatched interview
. 
. gen mismatched=.
{txt}(262 missing values generated)

{com}. recode mismatched(.=0) if russian==1 & prefruss==1
{txt}(mismatched: 46 changes made)

{com}. recode mismatched(.=0) if russian==0 & prefruss==0
{txt}(mismatched: 80 changes made)

{com}. 
. recode mismatched (.=1) if russian==1 & prefruss==0
{txt}(mismatched: 100 changes made)

{com}. recode mismatched (.=1) if russian==0 & prefruss==1
{txt}(mismatched: 36 changes made)

{com}. 
. ologit integration russian mismatched

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.38274}  
Iteration 2:{space 3}log likelihood = {res:-310.38137}  
Iteration 3:{space 3}log likelihood = {res:-310.38137}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      3.71
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1568
{txt}Log likelihood = {res}-310.38137{txt}{col 49}Pseudo R2{col 67}= {res}    0.0059

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .3447835{col 26}{space 2} .2544724{col 37}{space 1}    1.35{col 46}{space 3}0.175{col 54}{space 4}-.1539732{col 67}{space 3} .8435402
{txt}{space 2}mismatched {c |}{col 14}{res}{space 2} .1828805{col 26}{space 2} .2515328{col 37}{space 1}    0.73{col 46}{space 3}0.467{col 54}{space 4}-.3101148{col 67}{space 3} .6758758
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .1665726{col 26}{space 2} .1974991{col 54}{space 4}-.2205184{col 67}{space 3} .5536636
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.563372{col 26}{space 2} .2222466{col 54}{space 4} 1.127776{col 67}{space 3} 1.998967
{txt}       /cut3 {c |}{col 14}{res}{space 2} 2.859435{col 26}{space 2} .2918898{col 54}{space 4} 2.287341{col 67}{space 3} 3.431528
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ***Table SI.4.1, full results for Model 1 in the main text
. ologit integration russian

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.64682}  
Iteration 2:{space 3}log likelihood = {res:-310.64583}  
Iteration 3:{space 3}log likelihood = {res:-310.64583}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      3.18
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0747
{txt}Log likelihood = {res}-310.64583{txt}{col 49}Pseudo R2{col 67}= {res}    0.0051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .4165536{col 26}{space 2} .2346692{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.0433896{col 67}{space 3} .8764968
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .1113242{col 26}{space 2} .1818716{col 54}{space 4}-.2451377{col 67}{space 3}  .467786
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.505565{col 26}{space 2} .2067364{col 54}{space 4} 1.100369{col 67}{space 3}  1.91076
{txt}       /cut3 {c |}{col 14}{res}{space 2}  2.80099{col 26}{space 2} .2799122{col 54}{space 4} 2.252373{col 67}{space 3} 3.349608
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ***Table SI.5.1, adjusting for generational differences
. 
. gen adult91=0
{txt}
{com}. recode adult91(0=1) if age<=43
{txt}(adult91: 59 changes made)

{com}. tab adult91

    {txt}adult91 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        203       77.48       77.48
{txt}          1 {c |}{res}         59       22.52      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        262      100.00
{txt}
{com}. 
. ologit integration russian 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.64682}  
Iteration 2:{space 3}log likelihood = {res:-310.64583}  
Iteration 3:{space 3}log likelihood = {res:-310.64583}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      3.18
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0747
{txt}Log likelihood = {res}-310.64583{txt}{col 49}Pseudo R2{col 67}= {res}    0.0051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .4165536{col 26}{space 2} .2346692{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.0433896{col 67}{space 3} .8764968
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .1113242{col 26}{space 2} .1818716{col 54}{space 4}-.2451377{col 67}{space 3}  .467786
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.505565{col 26}{space 2} .2067364{col 54}{space 4} 1.100369{col 67}{space 3}  1.91076
{txt}       /cut3 {c |}{col 14}{res}{space 2}  2.80099{col 26}{space 2} .2799122{col 54}{space 4} 2.252373{col 67}{space 3} 3.349608
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit integration russian adult91

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.36615}  
Iteration 2:{space 3}log likelihood = {res:-310.36452}  
Iteration 3:{space 3}log likelihood = {res:-310.36452}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      3.74
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1542
{txt}Log likelihood = {res}-310.36452{txt}{col 49}Pseudo R2{col 67}= {res}    0.0060

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .4108258{col 26}{space 2} .2349056{col 37}{space 1}    1.75{col 46}{space 3}0.080{col 54}{space 4}-.0495807{col 67}{space 3} .8712324
{txt}{space 5}adult91 {c |}{col 14}{res}{space 2}-.2117157{col 26}{space 2} .2833271{col 37}{space 1}   -0.75{col 46}{space 3}0.455{col 54}{space 4}-.7670265{col 67}{space 3} .3435951
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .0615836{col 26}{space 2} .1934936{col 54}{space 4}-.3176569{col 67}{space 3} .4408241
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.459007{col 26}{space 2} .2156134{col 54}{space 4} 1.036412{col 67}{space 3} 1.881601
{txt}       /cut3 {c |}{col 14}{res}{space 2} 2.755385{col 26}{space 2} .2863502{col 54}{space 4} 2.194149{col 67}{space 3} 3.316621
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. **Table SI.7.1, exploring heterogeneous treatment effects
. 
. gen russprefruss=(russian*prefruss)
{txt}
{com}. 
. ologit integration russian

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.64682}  
Iteration 2:{space 3}log likelihood = {res:-310.64583}  
Iteration 3:{space 3}log likelihood = {res:-310.64583}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}1{txt}){col 67}= {res}      3.18
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0747
{txt}Log likelihood = {res}-310.64583{txt}{col 49}Pseudo R2{col 67}= {res}    0.0051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .4165536{col 26}{space 2} .2346692{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.0433896{col 67}{space 3} .8764968
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .1113242{col 26}{space 2} .1818716{col 54}{space 4}-.2451377{col 67}{space 3}  .467786
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.505565{col 26}{space 2} .2067364{col 54}{space 4} 1.100369{col 67}{space 3}  1.91076
{txt}       /cut3 {c |}{col 14}{res}{space 2}  2.80099{col 26}{space 2} .2799122{col 54}{space 4} 2.252373{col 67}{space 3} 3.349608
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit integration russian prefruss russprefruss

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-312.23396}  
Iteration 1:{space 3}log likelihood = {res:-310.35758}  
Iteration 2:{space 3}log likelihood = {res:-310.35605}  
Iteration 3:{space 3}log likelihood = {res:-310.35605}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       262
{txt}{col 49}LR chi2({res}3{txt}){col 67}= {res}      3.76
{txt}{col 49}Prob > chi2{col 67}= {res}    0.2891
{txt}Log likelihood = {res}-310.35605{txt}{col 49}Pseudo R2{col 67}= {res}    0.0060

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} integration{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}russian {c |}{col 14}{res}{space 2} .5218183{col 26}{space 2} .2811839{col 37}{space 1}    1.86{col 46}{space 3}0.063{col 54}{space 4}-.0292919{col 67}{space 3} 1.072929
{txt}{space 4}prefruss {c |}{col 14}{res}{space 2}  .116915{col 26}{space 2} .3867549{col 37}{space 1}    0.30{col 46}{space 3}0.762{col 54}{space 4}-.6411106{col 67}{space 3} .8749407
{txt}russprefruss {c |}{col 14}{res}{space 2}-.3484487{col 26}{space 2}  .509854{col 37}{space 1}   -0.68{col 46}{space 3}0.494{col 54}{space 4}-1.347744{col 67}{space 3} .6508467
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       /cut1 {c |}{col 14}{res}{space 2} .1461325{col 26}{space 2} .2170302{col 54}{space 4} -.279239{col 67}{space 3} .5715039
{txt}       /cut2 {c |}{col 14}{res}{space 2} 1.543355{col 26}{space 2} .2390081{col 54}{space 4} 1.074907{col 67}{space 3} 2.011802
{txt}       /cut3 {c |}{col 14}{res}{space 2} 2.839238{col 26}{space 2}  .305072{col 54}{space 4} 2.241308{col 67}{space 3} 3.437169
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
{txt}end of do-file

{com}. exit, clear
